Strava activities - Analysis, investigation and visualization of two years of recorded efforts

Data loading

Which are the longest activities in term of time and length? Let's pick the top 5 for both aspects.

Let's check start and arrival points of my longest trip, the activity n° 91.

Starting and arrival point are quite near. This could be a ring trip, but let's check it out by plotting it.

Activity visualization(s)

So apparently this wasn't a ring trip, but an a/r trip to Garda Lake. Let's investigate more about it.

20 km/h as average pace isn't so bad, but 51 km/h it's definitely out of my capabilities. Where can I have had that peak?

We can see that from Nago to Torbole there is a street portion in which I had a huge pace in a direction, but a really low one in the other direction. Why that?

Excluding the last point, all the others are sequential. This indicates a particular portion of the route where I reached that pace. Could you guess the reason?

That's why: 86m of height difference in less than a km, it's a quite steep descent! But truth be told, I still have clear memories about the ascent on our way back..

Activities visualization - first attempt

Plot all hike activities in a map. HVplot guarantees a pleasant visualization, but with hikes it's pointless to find clusters of activities. In any case, this is a good example of how trajectories can be mapped together and be easily identified when not overlapped.

On the other hand, with too many overlapping activities it's complicated to identify how many of them are in a given area (even colours could be misleading). We can isolate starting points and plot them to have a better idea.

With a scatter plot of the starting points we can have an idea of how they are distributed.

Clustering activities

As predictable, most activities have been started from Trento. It would be pointless to carry out more analysis at this level, but we can check the distribution over the city area.

It's possible to see a first pattern: most of the activities started in the south-west part of the city, near the Adige river. Is it possible to better understand this?

This visualization confirm the main area of starting places. Can we infer something more with a clustering? Maybe the area where I live?

Using a dbscan technique it's clear that there are three main areas of starting points: two belongs to the Lungadige, while the other is located in San Pio X neighbourhood. So, assuming that I'm not living on the river, I probably live in the third area found (which is a right guess).

Strava-like heatmap visualization

For a further visualization, let's check out an heatmap of all the activities loaded.

Thanks to Folium, there is a representation with a heatmap of all the activities. It's easy to notice a greater concentration of points in the areas highlighted before.

Vigolana Hike - Analysis with OSM

Hiking activities could be interesting to analyze. For example, given that I'm not a good biker (or a good trail runner...yet), activities with an high elevation difference between highest and lowest points should be hikes.

Stops analysis

For example, activity n°115 has been a hike to the Vigolana Shelter (Madonnina) made last summer. Did I took any stop on my way up? Was them for any specific reason?

Let's see where these stops have been taken along the hike.

A possible cause for the stops could be the high elevation gain made in a short time. Let's check if it's the case.

In some cases stops could explained by elevation gain in a short amount of time, but in other there should be different reasons. A good viewpoint to take pictures while resting, maybe? Let's check with the longest stop I took.

Including OSM data for the analysis

Apparently, I stopped for a short break, but also to take a nice picture and enjoy the view. Let's confirm it in the map seen before, but changing the layer with a more appropriate one.

As expected, with the OSM layer we can see that the longest stop has been taken in proximity (within 10m) of the viewpoint Polsa.
Fun fact: this viewpoint has been mapped last time in 2020 by the user Martin Larcher (https://www.openstreetmap.org/node/910787221); at the end of the hike we just analyzed, I spent the night in the Madonnina shelter with...Martin Larcher himself, along with his family!

Performance analysis

Let's look into another aspect of running activities: running performances over time. Was there performance difference over time? How can they be measured?

Getting average pace and runs' lengths

Exploiting VO2Max data

VO2Max is a measure of maximum oxygen consumption per minute for any muscle contraction. This is a biological parameter which can be partially improved by trainings. Was I able to modify it through my activities? When did it decrease?

Efforts comparison

There are some patterns that could be noticed: